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The Impact of Covid-19 Economic Shock on Inequality and Poverty in Mexico

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The Impact of Covid-19 Economic Shock on Inequality and Poverty in Mexico THE IMPACT OF COVID-19 ECONOMIC SHOCK ON INEQUALITY AND POVERTY IN MEXICO Nora Lustig and Valentina Martinez Pabon Working Paper 98 1 October, 2020 The CEQ Working Paper Series The CEQ Institute at Tulane University works to reduce inequality and poverty through rigorous tax and benefit incidence analysis and active engagement with the policy community. The studies published in the CEQ Working Paper series are pre-publication versions of peer-reviewed or scholarly articles, book chapters, and reports produced by the Institute. The papers mainly include empirical studies based on the CEQ methodology and theoretical analysis of the impact of fiscal policy on poverty and inequality. The content of the papers published in this series is entirely the responsibility of the author or authors. Although all the results of empirical studies are reviewed according to the protocol of quality control established by the CEQ Institute, the papers are not subject to a formal arbitration process. Moreover, national and international agencies often update their data series, the information included here may be subject to change. For updates, the reader is referred to the CEQ Standard Indicators available online in the CEQ Institute’s website www.commitmentoequity.org/datacenter. The CEQ Working Paper series is possible thanks to the generous support of the Bill & Melinda Gates Foundation. For more information, visit www.commitmentoequity.org. The CEQ logo is a stylized graphical representation of a Lorenz curve for a fairly unequal distribution of income (the bottom part of the C, below the diagonal) and a concentration curve for a very progressive transfer (the top part of the C). THE IMPACT OF COVID-19 ECONOMIC SHOCK * ON INEQUALITY AND POVERTY IN MEXICO Nora Lustig and Valentina Martinez Pabon† CEQ Working Paper 98 OCTOBER 2020 ABSTRACT Based on the economic sector in which household members work, we use microsimulation to estimate the distributional consequences of the COVID-19 pandemic in Mexico. Although the predicted increase in poverty is significant, we find that the worst effects may not be on the poorest, but those (roughly) in the middle deciles of the ex ante income distribution: the moderate poor and those vulnerable to falling below the poverty line if subject to an adverse shock. We estimate that the economic shock could induce significantly less increase in poverty in rural areas and among the indigenous population. The increase in poverty seems to be similar for male- and female-headed households. Compared to other countries, Mexico stands out because of the absence of mitigation policies. In contrast, in Argentina and Brazil, the expanded social assistance seems to significantly offset the impact of the economic dislocation. JEL Codes: C63, D31, I32, I38 Keywords: COVID-19, inequality, poverty, mobility, microsimulations, Latin America, Mexico * This paper will appear in Estudios Económicos - Número Especial Sobre la Economía Mexicana coordinated by Gerardo Esquivel and Susan Parker, 2021. This paper draws from N. Lustig, V. Martinez Pabon, F. Sanz and S. D. Younger (2020). “The Impact of COVID-19 Lockdowns and Expanded Social Assistance on Inequality, Poverty and Mobility in Argentina, Brazil, Colombia and Mexico.” COVID Economics: Vetted and Real-Time Papers, Issue 46, Center for Economic Policy Research (CEPR), 2020. However, in contrast to the former, we include two additional sources of income: consumption of own production and imputed rent. In addition, we carry out the analysis not only at the national level but also by urban and rural areas. The authors are grateful to Raymundo Campos and John Scott for their very useful suggestions. This paper was prepared as part of the Commitment to Equity Institute’s country-cases research program and benefitted from the generous support of the Bill & Melinda Gates Foundation. For more details, click here www.ceqinstitute.org. † Nora Lustig is Samuel Z. Stone Professor of Latin American Economics in the Department of Economics at Tulane University, and Director of the Commitment to Equity Institute at Tulane University ([email protected]). Valentina Martinez Pabon is a Ph.D. student in the Department of Economics at Tulane University ([email protected]). The Impact of COVID-19 Economic Shock on Inequality and Poverty in Mexico* Nora Lustig and Valentina Martinez Pabon† October 2020 Abstract Based on the economic sector in which household members work, we use microsimulation to estimate the distributional consequences of the COVID-19 pandemic in Mexico. Although the predicted increase in poverty is significant, we find that the worst effects may not be on the poorest, but those (roughly) in the middle deciles of the ex ante income distribution: the moderate poor and those vulnerable to falling below the poverty line if subject to an adverse shock. We estimate that the economic shock could induce significantly less increase in poverty in rural areas and among the indigenous population. The increase in poverty seems to be similar for male- and female-headed households. Compared to other countries, Mexico stands out because of the absence of mitigation policies. In contrast, in Argentina and Brazil, the expanded social assistance seems to significantly offset the impact of the economic dislocation. JEL Codes: C63, D31, I32, I38 Keywords: COVID-19, inequality, poverty, mobility, microsimulations, Latin America, Mexico * This paper will appear in Estudios Económicos - Número Especial Sobre la Economía Mexicana coordinated by Gerardo Esquivel and Susan Parker, 2021. This paper draws from N. Lustig, V. Martinez Pabon, F. Sanz and S. D. Younger (2020). “The Impact of COVID-19 Lockdowns and Expanded Social Assistance on Inequality, Poverty and Mobility in Argentina, Brazil, Colombia and Mexico.” COVID Economics: Vetted and Real-Time Papers, Issue 46, Center for Economic Policy Research (CEPR), 2020. However, in contrast to the former, we include two additional sources of income: consumption of own production and imputed rent. In addition, we carry out the analysis not only at the national level but also by urban and rural areas. The authors are grateful to Raymundo Campos and John Scott for their very useful suggestions. † Nora Lustig is Samuel Z. Stone Professor of Latin American Economics in the Department of Economics at Tulane University, and Director of the Commitment to Equity Institute at Tulane University ([email protected]). Valentina Martinez Pabon is a Ph.D. student in the Department of Economics at Tulane University ([email protected]). 1. Introduction The recent COVID-19 pandemic has come at overwhelming health and economic costs to Latin America, Mexico in particular 1.In August 2020, Mexico was among the top ten countries in terms of infections and the top five in terms of deaths per one-hundred thousand inhabitants.2 To contain the spread of the virus, governments implemented lockdown policies of various degrees.3 Although in Mexico, the federal government did not implement full-lockdown measures, “stay-at-home” recommendations were put in place. Inevitably, these measures caused a sharp reduction of activity, a fall in employment and income, and a rise in poverty and inequality.4 In this paper we analyze the impact of the economic dislocation on poverty, inequality, and income mobility in Mexico, and compare it with the impacts in the three other largest Latin American countries: Argentina, Brazil and Colombia.5 In addition to lockdowns to control infection rates, governments in these three countries have introduced new or expanded social assistance measures to varying degrees. In Mexico, there has been no such expansion. Based on the economic sector in which household members work, we use microsimulation to estimate potential income losses at the household level, using ENIGH (2018).6 The simulations first identify individuals whose income is “at risk” because they work in sectors in which COVID-19 has reduced or eliminated activity. We base our determination of at-risk income on the economic sectors in which one works. We assume that income derived from work in sectors that are “essential” is not at risk, while any income earned in “nonessential” sectors is at risk. For Mexico we use the ILO definition of essential sectors. We aggregate this at-risk income to the household level and then simulate actual losses using a range of two key parameters: the share of households with at-risk income that actually lose income and, of those who lose income, the share of at-risk income lost. We allow both parameters to range from zero to one-hundred percent, yielding one-hundred possible outcomes. To narrow our focus to reasonable possibilities, we choose a combination of the two key parameters that yields a 1 IMF (2020). 2 https://coronavirus.jhu.edu/data/mortality. 3 For a description of lockdowns by country see, for example, Pages et al. (2020). 4 According to IMF (2020) and ECLAC (2020), the region’s GDP could contract in 2020 by 9.4 and 9.1 percent, respectively. 5 Note that mobility here refers to ex ante/ex post comparisons and not to mobility over time or intergenerational mobility. 6 Our exercise falls under the definition of microsimulation by the International Microsimulation Association. Namely: The International Microsimulation Association defines microsimulation as a modelling technique that operates at the level of individual units such as persons, households, vehicles or firms. Within the model each unit is represented by a record containing a unique identifier and a set of associated attributes – e.g. a list of persons with known age, sex, marital and employment status; or a list of vehicles with known origins, destinations and operational characteristics. A set of rules (transition probabilities) are then applied to these units leading to simulated changes in state and behavior. These rules may be deterministic (probability = 1), such as changes in tax liability resulting from changes in tax regulations, or stochastic (probability <=1), such as chance of dying, marrying, giving birth or moving within a given time period.
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